It is desirable to identify an object in a video and track the movement of that object across a plurality of frames in the video sequence. Prior efforts in this regard have focused on motion-based, shape-based, color-based tracking or a combination of those methods. Such methods are easily confused and suffer performance degradation in the presence of other object(s) of similar size/shape/motion/color in the vicinity of the object of interest, or a partial occlusion of the object, or a change of pose. Shadows can be particularly confusing to prior art methods because the shadow moves in the video sequence along with the object.
Spectral imaging deals with imaging spectral bands over a spectral range, and produces the spectra of all pixels in the captured scene. A primary advantage to spectral imaging is that, because an entire spectrum is acquired at each point and the wavelengths are known, post-processing allows other available information from a dataset to be mined such as type of material. Disadvantages are cost and complexity. Data storage capacity can be significant since spectral images. A need exists to apply spectral imaging to facilitate object identification and tracking without noticeably increasing the cost and computational complexity.
Accordingly, what is needed in this art are systems and methods for identifying materials comprising an object captured in a video and for using the identified materials to track that object as it moves across the captured video scene.